What is your Data EQ?

There is a common misconception about data-informed decision making. It goes that once we implement the right tools, and figure out how to analyze the data correctly, the data will automatically turn into insights and will translate to better business decisions. It sounds great in theory. But in practice, even if you have the best data strategy in the world, there are a lot of competencies and processes that are required, which utilize both hard and soft skills, to fully get the value out of your data to make better decisions. Failure in one of these areas can mean disaster to your ability to make data-informed decisions.

Data-informed decision-making is the ability to transform information into actionable and verified knowledge to ultimately make business decisions. This means you need the skills to identify problems, frame questions, collect the required data, transform that data into information and knowledge, transform that knowledge into decisions, communicate and act on those decisions, and finally evaluate the decisions.

A recent PwC CEO survey found that 77% of the 1,400 CEOs surveyed highlighted soft skills as the biggest threat to today’s business. With the rise of the digital age and digital transformation, hard skills are increasing in their importance too. But the companies that embrace and foster the culture and development of soft skills will be the ones that survive. Let’s look at a few soft skills required to make data-informed decisions.

Collaboration

When making a decision, it is important to consider as many aspects of the decision as possible and work collaboratively. This is because other people will have different experiences, possibly leading to different information and knowledge, which could impact your decision. Two people may have access to the same data and information, but their experiences will be different, which can lead to different insights.Collaborative decision making is critical to ensure you are working systemically in an organization.

Creativity and curiosity

Creativity and curiosity are important when making decisions, because it helps to come up with multiple options and find a great solution that will support the overall success in a business. Decisions should be thought through to understand all the implications. You should have a hypothesis about your decisions and then try to disprove it. Too often we have a gut feel for how things will play out and we reach out to data to support that feeling, not to contradict it. This is where creativity can come into play as you should use that, combined with problem solving, to try to find reasons why your decision will not work, before you fully embrace it.

Critical thinking and self-awareness

The skills of creativity and curiosity combined with critical thinking and self-awareness allow decision makers to avoid bias. Bias, or cognitive bias, is a mistake in reasoning, evaluating, remembering, often occurring subconsciously as a result of the decision maker holding on to their preferences and beliefs regardless of contrary data and information.

Decision makers can reduce bias by challenging the status quo, seeking multiple perspectives (collaboration), searching for more data and information (curious and skeptical of the data), play devil’s advocate with your hypothesis, and most importantly reflect on your own views and values, and identify if they are getting in the way of your decision.

Analytic Storytelling

Effectively communicating your insights using data is key to ensure others understand your insights. This includes an approach called analytic storytelling. This is the process of bringing data to life to tell a well-constructed narrative.Use the right data, including just the right visualizations to support your decisions, along with the right amount of storytelling to get your message across at the right level.

Want to learn more about how to make data-informed decisions? Take a look at our free Qlik Continuous Classroom learning module on the topic.

Want to learn how to make data-informed decisions? They key is leveraging both hard skills and soft skills with data!